Fellow Project
2024–2025
Human-AI-Robot Collaboration for Accelerated Energy Transition Self-Driving Chemistry Lab
Project by
This project leverages advanced automation, artificial intelligence, and robotics to catalyze the conversion of carbon dioxide (CO₂) into high-value chemical feedstocks, thereby advancing global sustainability goals. By integrating a self-driving laboratory with a curated library of photocatalyst materials, Milad and colleaques aim to rapidly identify and refine catalysts for highly efficient CO₂ reduction. The proposed approach combines advanced flow reactor engineering with real-time, data-driven modeling and decision-making to systematically optimize catalyst performance and reaction conditions. This innovative framework streamlines CO₂ conversion pathways, minimizes environmental impact, and drives the development of cleaner, more sustainable energy solutions.
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